An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis
- Guanjue Xiang1,10,
- Cheryl A. Keller1,10,
- Elisabeth Heuston2,
- Belinda M. Giardine1,
- Lin An1,
- Alexander Q. Wixom1,
- Amber Miller1,
- April Cockburn1,
- Michael E.G. Sauria3,
- Kathryn Weaver3,
- Jens Lichtenberg2,
- Berthold Göttgens4,
- Qunhua Li5,
- David Bodine2,
- Shaun Mahony1,
- James Taylor3,
- Gerd A. Blobel6,
- Mitchell J. Weiss7,
- Yong Cheng7,
- Feng Yue8,
- Jim Hughes9,
- Douglas R. Higgs9,
- Yu Zhang5 and
- Ross C. Hardison1
- 1Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
- 2NHGRI Hematopoiesis Section, Genetics and Molecular Biology Branch, National Institutes of Health, Bethesda, Maryland 20892, USA;
- 3Departments of Biology and Computer Science, Johns Hopkins University, Baltimore, Maryland 20218, USA;
- 4Welcome and MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge CB2 1TN, United Kingdom;
- 5Department of Statistics, Program in Bioinformatics and Genomics, Center for Computational Biology and Bioinformatics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
- 6Department of Pediatrics, Children's Hospital of Philadelphia and University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA;
- 7Department of Hematology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA;
- 8Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033, USA;
- 9MRC Weatherall Institute of Molecular Medicine, Oxford University, Oxford OX3 9DS, United Kingdom
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↵10 These authors contributed equally to this work.
Abstract
Thousands of epigenomic data sets have been generated in the past decade, but it is difficult for researchers to effectively use all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for validated systematic integration of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By using IDEAS as our integrative and discriminative epigenome annotation system, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of more than 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website to aid research in genomics and hematopoiesis.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.255760.119.
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Freely available online through the Genome Research Open Access option.
- Received August 9, 2019.
- Accepted February 21, 2020.
This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
